code: def test_hyperparameter_existence_and_defaults():
      hp = hp_module.HyperParameters()
      hypermodel = efficientnet.HyperEfficientNet(
          input_shape=INPUT_SHAPE_224, classes=10
      )
      hypermodel.build(hp)
      assert hp.get("version") == "B0"
      assert hp.get("top_dropout_rate") == 0.2
      assert hp.get("learning_rate") == 0.01
      assert hp.get("pooling") == "avg"
  
file_path: keras-tuner/keras_tuner/applications/efficientnet_test.py
imports: import numpy
  import pytest
  from keras_tuner.applications import efficientnet
  from keras_tuner.backend import config
  from keras_tuner.backend import keras
  from keras_tuner.engine import hypermodel
  from keras_tuner.engine import hyperparameters
label_desc: Use image node_id 2 for calling a global function with example usage: test_hyperparameter_existence_and_defaults() without return types